<html><head><title>Data Scientist - Seattle, WA</title></head>
<body><h2>Data Scientist - Seattle, WA</h2>
<ul><li>Bachelor's Degree in any quantitative discipline such as Statistics, Mathematics, Economics, Computer Science, Operational Research, or a related quantitative field</li><li>3+ years of experience working in Analytics / Business Intelligence environment</li><li>3+ years professional experience in modeling and statistical analysis of large data sets</li><li>Proven experience in working with databases and SQL in a business environment</li><li>Demonstrated use of analytical packages and query languages such as SAS, SPSS and SQL</li><li>Proven experience in design and execution of analytical projects</li><li>Demonstrated experience working in large scale databases and data warehouses</li><li>Track record of developing and implementing models using programming and scripting (Java, Python, R, Ruby, C/C++, or Matlab)</li></ul>

We are growing and taking on more to make the world safe for ecommerce. Amazon.com's TRMS team is a centralized technology team that works to make Amazon the safest and most trusted marketplace online and offline for our Buyers and Sellers by defending Amazon accounts from malicious actors. These systems, invisible to the customer, work seamlessly across the billions of transactions occurring simultaneously around the world. Come build with us! Because of Amazon's huge scale, this a great opportunity to add hundreds of millions to the bottom line and protect Customers everywhere.<br/>
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We are seeking an innovative, results-oriented, customer-centric data scientist to drive expansion of innovative ML solutions globally in the Account Integrity space. As a Data Scientist, you will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences.<br/>
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Responsibilities:<br/>
<ul><li>Use predictive analytics and machine learning techniques to solve complex problems and drive business decisions</li><li>Employ the appropriate algorithms to discover patterns of risks, abuse and help reduce bad actor activity</li><li>Design experiments, test hypotheses, and build actionable models to optimize TRMS operations</li><li>Solve analytical problems, and effectively communicate methodologies and results</li><li>Build predict models to forecast risks for product launches and operations</li><li>Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies</li><li>Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area</li></ul>

<li>Master's degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least 2 years of working experience as a Data Scientist</li><li>Experience/knowledge of advanced machine learning techniques such as GBM, random forest, etc</li><li>Experience in e-commerce / on-line companies in fraud / risk control functions</li><li>Coding skills in one of the modern languages Java, Python, Scala, R</li><li>Experience with visualization technologies such as Tableau</li><li>Experience in statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and natural language processing, experimental design, social networking analysis, feature engineering, etc</li><li>Compelling communication and influencing skills and participation with demonstrated experience engaging and influencing senior executives</li><li>Strong analytical and quantitative skills with the ability to use data and metrics to back up assumptions, recommendations and drive actions</li></body>
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